:doc:`Bedrock <../../bedrock>` / Client / get_model_invocation_job

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get_model_invocation_job
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.. py:method:: Bedrock.Client.get_model_invocation_job(**kwargs)

  

  Gets details about a batch inference job. For more information, see `Monitor batch inference jobs <https://docs.aws.amazon.com/bedrock/latest/userguide/batch-inference-monitor>`__

  

  See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/bedrock-2023-04-20/GetModelInvocationJob>`_  


  **Request Syntax**
  ::

    response = client.get_model_invocation_job(
        jobIdentifier='string'
    )
    
  :type jobIdentifier: string
  :param jobIdentifier: **[REQUIRED]** 

    The Amazon Resource Name (ARN) of the batch inference job.

    

  
  
  :rtype: dict
  :returns: 
    
    **Response Syntax**

    
    ::

      {
          'jobArn': 'string',
          'jobName': 'string',
          'modelId': 'string',
          'clientRequestToken': 'string',
          'roleArn': 'string',
          'status': 'Submitted'|'InProgress'|'Completed'|'Failed'|'Stopping'|'Stopped'|'PartiallyCompleted'|'Expired'|'Validating'|'Scheduled',
          'message': 'string',
          'submitTime': datetime(2015, 1, 1),
          'lastModifiedTime': datetime(2015, 1, 1),
          'endTime': datetime(2015, 1, 1),
          'inputDataConfig': {
              's3InputDataConfig': {
                  's3InputFormat': 'JSONL',
                  's3Uri': 'string',
                  's3BucketOwner': 'string'
              }
          },
          'outputDataConfig': {
              's3OutputDataConfig': {
                  's3Uri': 'string',
                  's3EncryptionKeyId': 'string',
                  's3BucketOwner': 'string'
              }
          },
          'vpcConfig': {
              'subnetIds': [
                  'string',
              ],
              'securityGroupIds': [
                  'string',
              ]
          },
          'timeoutDurationInHours': 123,
          'jobExpirationTime': datetime(2015, 1, 1)
      }
      
    **Response Structure**

    

    - *(dict) --* 
      

      - **jobArn** *(string) --* 

        The Amazon Resource Name (ARN) of the batch inference job.

        
      

      - **jobName** *(string) --* 

        The name of the batch inference job.

        
      

      - **modelId** *(string) --* 

        The unique identifier of the foundation model used for model inference.

        
      

      - **clientRequestToken** *(string) --* 

        A unique, case-sensitive identifier to ensure that the API request completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see `Ensuring idempotency <https://docs.aws.amazon.com/AWSEC2/latest/APIReference/Run_Instance_Idempotency.html>`__.

        
      

      - **roleArn** *(string) --* 

        The Amazon Resource Name (ARN) of the service role with permissions to carry out and manage batch inference. You can use the console to create a default service role or follow the steps at `Create a service role for batch inference <https://docs.aws.amazon.com/bedrock/latest/userguide/batch-iam-sr.html>`__.

        
      

      - **status** *(string) --* 

        The status of the batch inference job.

         

        The following statuses are possible:

         

        
        * Submitted – This job has been submitted to a queue for validation.
         
        * Validating – This job is being validated for the requirements described in `Format and upload your batch inference data <https://docs.aws.amazon.com/bedrock/latest/userguide/batch-inference-data.html>`__. The criteria include the following: 

          
          * Your IAM service role has access to the Amazon S3 buckets containing your files.
           
          * Your files are .jsonl files and each individual record is a JSON object in the correct format. Note that validation doesn't check if the ``modelInput`` value matches the request body for the model.
           
          * Your files fulfill the requirements for file size and number of records. For more information, see `Quotas for Amazon Bedrock <https://docs.aws.amazon.com/bedrock/latest/userguide/quotas.html>`__.
          

        
         
        * Scheduled – This job has been validated and is now in a queue. The job will automatically start when it reaches its turn.
         
        * Expired – This job timed out because it was scheduled but didn't begin before the set timeout duration. Submit a new job request.
         
        * InProgress – This job has begun. You can start viewing the results in the output S3 location.
         
        * Completed – This job has successfully completed. View the output files in the output S3 location.
         
        * PartiallyCompleted – This job has partially completed. Not all of your records could be processed in time. View the output files in the output S3 location.
         
        * Failed – This job has failed. Check the failure message for any further details. For further assistance, reach out to the `Amazon Web Services Support Center <https://console.aws.amazon.com/support/home/>`__.
         
        * Stopped – This job was stopped by a user.
         
        * Stopping – This job is being stopped by a user.
        

        
      

      - **message** *(string) --* 

        If the batch inference job failed, this field contains a message describing why the job failed.

        
      

      - **submitTime** *(datetime) --* 

        The time at which the batch inference job was submitted.

        
      

      - **lastModifiedTime** *(datetime) --* 

        The time at which the batch inference job was last modified.

        
      

      - **endTime** *(datetime) --* 

        The time at which the batch inference job ended.

        
      

      - **inputDataConfig** *(dict) --* 

        Details about the location of the input to the batch inference job.

        .. note::    This is a Tagged Union structure. Only one of the     following top level keys will be set: ``s3InputDataConfig``.     If a client receives an unknown member it will     set ``SDK_UNKNOWN_MEMBER`` as the top level key,     which maps to the name or tag of the unknown     member. The structure of ``SDK_UNKNOWN_MEMBER`` is     as follows::

                'SDK_UNKNOWN_MEMBER': {'name': 'UnknownMemberName'}


      
        

        - **s3InputDataConfig** *(dict) --* 

          Contains the configuration of the S3 location of the input data.

          
          

          - **s3InputFormat** *(string) --* 

            The format of the input data.

            
          

          - **s3Uri** *(string) --* 

            The S3 location of the input data.

            
          

          - **s3BucketOwner** *(string) --* 

            The ID of the Amazon Web Services account that owns the S3 bucket containing the input data.

            
      
    
      

      - **outputDataConfig** *(dict) --* 

        Details about the location of the output of the batch inference job.

        .. note::    This is a Tagged Union structure. Only one of the     following top level keys will be set: ``s3OutputDataConfig``.     If a client receives an unknown member it will     set ``SDK_UNKNOWN_MEMBER`` as the top level key,     which maps to the name or tag of the unknown     member. The structure of ``SDK_UNKNOWN_MEMBER`` is     as follows::

                'SDK_UNKNOWN_MEMBER': {'name': 'UnknownMemberName'}


      
        

        - **s3OutputDataConfig** *(dict) --* 

          Contains the configuration of the S3 location of the output data.

          
          

          - **s3Uri** *(string) --* 

            The S3 location of the output data.

            
          

          - **s3EncryptionKeyId** *(string) --* 

            The unique identifier of the key that encrypts the S3 location of the output data.

            
          

          - **s3BucketOwner** *(string) --* 

            The ID of the Amazon Web Services account that owns the S3 bucket containing the output data.

            
      
    
      

      - **vpcConfig** *(dict) --* 

        The configuration of the Virtual Private Cloud (VPC) for the data in the batch inference job. For more information, see `Protect batch inference jobs using a VPC <https://docs.aws.amazon.com/bedrock/latest/userguide/batch-vpc>`__.

        
        

        - **subnetIds** *(list) --* 

          An array of IDs for each subnet in the VPC to use.

          
          

          - *(string) --* 
      
        

        - **securityGroupIds** *(list) --* 

          An array of IDs for each security group in the VPC to use.

          
          

          - *(string) --* 
      
    
      

      - **timeoutDurationInHours** *(integer) --* 

        The number of hours after which batch inference job was set to time out.

        
      

      - **jobExpirationTime** *(datetime) --* 

        The time at which the batch inference job times or timed out.

        
  
  **Exceptions**
  
  *   :py:class:`Bedrock.Client.exceptions.ResourceNotFoundException`

  
  *   :py:class:`Bedrock.Client.exceptions.AccessDeniedException`

  
  *   :py:class:`Bedrock.Client.exceptions.ValidationException`

  
  *   :py:class:`Bedrock.Client.exceptions.InternalServerException`

  
  *   :py:class:`Bedrock.Client.exceptions.ThrottlingException`

  